Suggestions
Balaji Viswanathan Ph.D.
CEO of Mitra AI at Invento Robotics
Balaji Viswanathan, Ph.D., is the CEO of Mitra Robot and a prominent figure in the field of robotics. He is based in the San Francisco Bay Area and has an extensive background in technology and entrepreneurship.
Education
- Ph.D. in Computer Science from the University of Maryland Baltimore County, where he achieved a 4.0 GPA, focusing on computer vision.
- Master of Business Administration (MBA) from Babson College - Franklin W. Olin Graduate School of Business.
- Master's in Computer Science from the University of Maryland Baltimore County.
- Bachelor's in Computer Engineering from Thiagarajar College of Engineering.
Professional Experience
- CEO at Mitra Robot: Leading the development of humanoid robots designed for hospitality and customer interaction.
- Former Product Manager at Black Duck Software: Managed open source software solutions.
- Co-Founder of Invento Robotics: Established the company that developed Mitra Robot, which made its debut at the Global Entrepreneurship Summit in 2017.
- Software Design Engineer at Microsoft: Worked on various projects, including Windows operating systems and mobile technologies.
Contributions
Mitra Robot, which means "friend" in Hindi, is designed to enhance workplace productivity and customer engagement. It has been utilized in various sectors, including hospitality, healthcare, and events. The robot gained significant attention for its role in connecting patients with families during the COVID-19 pandemic.
Balaji is also passionate about teaching machines to think and has been involved in various entrepreneurial ventures throughout his career, showcasing his commitment to innovation in technology.12
Highlights
It's intriguing how in AI research papers, the results for new techniques almost always seem to hover around 90-95% accuracy. However, in practical applications, we know that none of the Retrieval-Augmented Generation (RAG) techniques come close to achieving that level of accuracy. Despite this, authors frequently claim near-perfect performance for their methods.
Whether it's MMLU or other major AI evaluation benchmarks, these metrics have become increasingly ineffective for truly assessing quality, as most leading tools are now clustering near the 100% mark.
What we desperately need are benchmarks that score Large Language Models (LLMs) and RAG techniques more realistically, providing insights that can genuinely guide deployment decisions.
A while ago a chance to have a dinner with Dr. Yunus, the Nobel laureate who is now heading Bangladesh. We discussed about future of developmental economics and impact from AI.
